Cross-layer resource allocation in wireless and optical networks

The success of the Internet can be largely attributed to its modular architecture and its high level of abstraction. As a result, the Internet is an extremely heterogeneous network in which a multitude of wireless, electronic, and optical devices coexist. Yet, wireless and optical technologies are approaching their capacity limits. In this thesis, we study cross-layer and cross-domain optimizations in wireless and optical networks to improve the scalability of heterogeneous networks. Specifically, we investigate the benefits in capacity improvement and energy efficiency of improved interaction between different layers, as well as different domains. First, we use the Local Pooling (LoP) conditions to identify all the network graphs under primary interference constraints in which Greedy Maximal Scheduling (GMS) achieves 100% throughput. In addition, we show that in all bipartite graphs of size up to 7 x— n, GMS is guaranteed to achieve 66% throughput. Finally, we study the performance of GMS in interference graphs and show that it can perform arbitrarily bad. We study the properties of evolving graphs of networks whose structure changes due to node mobility. We present several graph metrics that quantify change in an evolving graph sequence and apply these metrics to several sources of mobility. We relate our results on the effect of the rate of graph change to the performance of higher-layer network algorithms in dynamic networks. We then consider optical networks, and formulate a global optimization problem that captures the QoT constraints in future dynamic optical networks. We design a power control algorithm for solving this problem by using feedback from Optical Performance Monitors (OPMs). We evaluate this algorithm via extensive simulations on a network-scale optical network simulator, as well as experiments with commercial optical network equipment. Finally, we consider a cellular network with Coordinated Multi-Point (CoMP) Joint Transmission (JT) capabilities that allow multiple BSs to transmit simultaneously to a single user. We formulate the OFDMA Joint Scheduling (OJS) problem of determining a subframe schedule and deciding if to use JT, and we prove hardness results for this problem. Based on a decomposition framework, we develop efficient scheduling algorithms for bipartite and series-parallel planar graphs, and approximation algorithms for general graphs. We then consider a queueing model that evolves over time, and prove that solving the OJS problem with a specific queue-based utility function (in every subframe) achieves maximum throughput in CoMP-enabled networks.